Non-contact vital sign early warning device and method and storage medium

Abstract

The invention discloses a non-contact vital sign early warning device and method and a storage medium, and relates to the technical field of vital sign early warning, the non-contact vital sign early warning device comprises a vital sign monitoring device and a cloud server, the vital sign monitoring device comprises a respiratory rate detection module, and the cloud server is connected with the vital sign monitoring device. The respiratory rate detection module is used for calculating the respiratory rate; the heart rate detection module is used for calculating heartbeat frequency. The system has the advantages of being safe, reliable, high in accuracy and high in universality, and a guardian can capture the change trend of vital signs of a patient in the first time in a real-time monitoring mode, so that potential danger signals are found earlier, the illness state is pre-judged, and targeted measures are taken. Meanwhile, by analyzing a large amount of monitoring data for a long time, doctors can be helped to summarize rules and optimize diagnosis and treatment schemes, and the treatment success rate is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vital sign warning, and in particular to a non-contact vital sign warning device, method and storage medium. Background Art

[0002] One third of a person's life is spent in sleep, and the quality of sleep has a great impact on a person's health. During sleep, the body is in a resting state, and vital signs such as heart rate and breathing reflect the most basic health status of a person, and are also an important factor affecting the quality of sleep. If the heart rate is too fast or too slow, snoring or apnea, it may break the balance of the human body to maintain the normal operation of the body. Abnormal heart rate and breathing may make people panic, irritable, and difficult to calm down and fall asleep. Even if they fall asleep, they may easily wake up due to the discomfort of insufficient oxygen supply to the heart or breathing, resulting in a decrease in sleep quality. At the same time, long-term abnormal heart rate and breathing may bring psychological pressure and anxiety to people, and these negative emotions will further aggravate sleep problems, forming a vicious circle. Moreover, poor sleep may also affect the heart rate in turn. For example, long-term lack of sleep may lead to autonomic dysfunction and cause unstable heart rate. The existing breathing detection technology solution mainly uses a contact sensor device close to the chest or wrist to detect the degree of chest fluctuation and pulse to calculate vital sign information. The present invention collects the user's heart rate and respiratory rate in real time through a non-contact device, and then issues an early warning based on abnormal conditions of the respiratory rate and heart rate within a duration.

[0003] In the prior art, the contact detection method brings a sense of restraint and high complexity of data collection, and cannot achieve real-time warning and message push. For this reason, we propose a non-contact vital sign warning device, method and storage medium to solve the above problems. Summary of the invention

[0004] The object of the present invention is to provide a non-contact vital sign warning device, method and storage medium to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a non-contact vital sign warning device, the non-contact vital sign warning device comprising a vital sign monitoring device and a cloud server, the vital sign monitoring device comprising:

[0006] A respiratory rate detection module, wherein the respiratory rate detection module is used to calculate the respiratory frequency;

[0007] Heart rate detection module; the heart rate detection module is used to calculate the heart rate;

[0008] Early warning module; the early warning module is used to receive information about respiratory rate and heart rate and process it to obtain early warning information;

[0009] Transmission module; the transmission module is used to send the warning information notification obtained by the warning module to the cloud server;

[0010] The cloud server is used to store the respiratory rate and heart rate of the monitored person, and then correct and store the warning parameters, and periodically send them to the vital signs monitoring device for parameter replacement.

[0011] The cloud server is connected to the vital sign monitoring device via a wireless network, the respiratory rate detection module and the heart rate detection module are connected to the early warning module, and the early warning module is connected to the transmission module;

[0012] Among them, the transmission module includes a mobile communication module, a Wifi module, and a Bluetooth module.

[0013] Furthermore, a non-contact vital sign early warning method specifically comprises the following steps:

[0014] S1. When a person enters the detection range of the non-contact vital signs monitoring device and remains calm, the breathing rate of the person is monitored in real time by the breathing detection module, and the heart rate detection module is used to monitor the heart rate of the person in real time;

[0015] S2. Setting warning parameters, the warning module determines the current vital signs of the human body according to the respiratory rate and heart rate of the human body within the accumulated time period;

[0016] S3, uploading the current vital signs of the human body determined by the early warning module to the cloud server for early warning notification through the transmission module;

[0017] S4. The cloud server will store the respiratory rate and heart rate of the person being monitored for a long time, and then correct and store the warning parameters, and periodically send them to the vital signs monitoring device for replacement.

[0018] Further, in step S1, the respiratory rate detection module and the heart rate detection module include a non-contact radar signal transceiver mechanism and a digital signal processing, a pulse signal is transmitted through a radar transmission mechanism, and radar echo signal data is received; then the radar echo data is subjected to time domain slow time multi-stage filtering and frequency domain Fourier transform, and finally the respiratory frequency and the heart rate are calculated respectively by time domain peak finding and spectrum analysis, and the respiratory frequency and the heart rate are calculated respectively by time domain peak finding and spectrum analysis, specifically including the following processes;

[0019] Peak search in time domain: Use three cascaded second-order filters on slow-time echo data; the time interval between two peaks or two troughs is considered as a breathing cycle; when the calculated frequency is less than the minimum frequency or greater than the maximum frequency, the final breathing frequency is calculated using the average of multiple accumulated breathing frequencies;

[0020] Spectral analysis: Use 6-cascade second-order filtering of slow-time echo data; use EMD (empirical mode decomposition) to divide the processed data; estimate the final heart rate based on the accumulated heart rate spectrum.

[0021] Furthermore, in step S2, the determination of the current vital signs status of the human body includes the following process: setting a period of time T as a human vital signs observation period, when the respiratory rate exceeds a threshold value a1 during the observation period, and occurs more than a2 times, a high respiratory rate warning message is issued; when the respiratory rate is lower than a threshold value b1 during the observation period, and continues for more than b2 time, and occurs more than b3 times, a low respiratory rate warning message is issued; when the heart rate exceeds a threshold value c1 during the observation period, and occurs more than c2 times, a high heart rate warning message is issued; when the heart rate exceeds a threshold value d1 during the observation period, and occurs more than d2 times, a low heart rate warning message is issued.

[0022] Furthermore, in step S3, the transmission module uploads the information to the cloud server through one or more of the mobile communication module, Wifi module, and Bluetooth module for early warning notification.

[0023] Furthermore, in step S4, the cloud server receives the long-term respiratory rate and heart rate data of the human body through the early warning module, and corrects the respiratory rate and heart rate early warning parameter thresholds a1, b1, c1 and d1 of the human body, and archives the thresholds a1, b1, c1 and d1. At the same time, the thresholds a1, b1, c1 and d1 are sent to the vital signs monitoring device for replacement.

[0024] Furthermore, the determination of the current vital signs of the human body specifically includes the following determination process:

[0025] Get the time series data set of human heart rate and respiratory rate in the time period T, which are RR = {rr1, rr2, ..., rr n}, HR={hr1, hr2,..., hr m}, 1≤n, m≤T;

[0026] If Count(rr 1，...，n ≥a1)≥a2, that is, when the respiratory rate exceeds the threshold a1 during the observation period and exceeds a2 times, a high respiratory rate warning is issued;

[0027] If Count(rr 1，...，n ≤b1)≥b2, that is, when the respiratory rate is lower than the threshold value b1 within the observation period and exceeds b2 seconds continuously, and occurs more than b3 times, a low respiratory rate warning is issued;

[0028] If Count(hr 1，...，m ≥c1)≥c2, that is, when the heart rate exceeds the threshold value c1 during the observation period and exceeds c2 times, a high heart rate warning is triggered;

[0029] If Count(hr 1，...，m ≤d1)≥d2, that is, when the heart rate during the observation period is lower than the threshold d1 and occurs more than d2 times, a low heart rate warning is issued.

[0030] Furthermore, the cloud server will receive the vital sign data of a single user's sleep at night collected by vital sign monitoring equipment every day, and after removing abnormal data, calculate the minimum and maximum values ​​of two types of important parameter indicators, and then accumulate the important parameter indicator values ​​for a period of time to fuse and calculate the early warning parameters, and finally retain the early warning parameters on the cloud server side to periodically correct the respiratory rate and heart rate early warning parameters. For example, extract the user's vital sign data from 22:00 to 06:00 on a single day, divide the respiratory rate and heart rate data sets according to the decile method, remove the data in the first decile and the tenth decile, and then calculate the minimum and maximum values ​​of the respiratory rate data set, and the minimum and maximum values ​​of the heart rate data set; take a month as the time interval as the fusion calculation period, calculate the four average values ​​of the two important parameters of "minimum respiratory rate", "maximum respiratory rate", "minimum heart rate" and "maximum heart rate" within the interval days, and use them as respiratory rate warning parameters a1, b1 and heart rate warning parameters c1, d1 respectively; finally, periodically calculate and correct the respiratory rate and heart rate warning parameters according to the set time interval. In addition, after each correction, the cloud server will send instructions to the corresponding user's vital sign monitoring device and replace the warning parameter values ​​of the local warning module system.

[0031] Further, an electronic device includes a processor and a storage device;

[0032] The storage device stores a computer program, and the processor executes the computer program to perform the above-mentioned vital sign warning method.

[0033] Furthermore, a computer storage medium includes a computer program and data stored therein, and the computer program implements the above-mentioned vital sign warning method when executed by the processor.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. It is safe, reliable, accurate and universal. The real-time monitoring method enables the guardian to capture the changing trend of the patient's vital signs at the first time, so as to find potential danger signals earlier, predict the condition and take targeted measures. At the same time, by analyzing a large amount of monitoring data over a long period of time, it can also help doctors summarize the rules, optimize the diagnosis and treatment plan, and further improve the success rate of treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic block diagram of the non-contact vital sign warning device in the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] A non-contact vital sign warning device, the non-contact vital sign warning device includes a vital sign monitoring device 7 and a cloud server 8, the cloud server 8 is used to store the respiratory rate and heart rate of the monitored person, and then correct and store the warning parameters, and periodically send them to the vital sign monitoring device 7 for parameter replacement, the vital sign monitoring device 7 includes:

[0039] A respiratory rate detection module 1, the respiratory rate detection module 1 is used to calculate the respiratory frequency;

[0040] Heart rate detection module 2: Heart rate detection module 2 is used to calculate the heart rate;

[0041] Warning module 3: Warning module 3 is used to receive information about respiratory rate and heart rate and process it to obtain warning information;

[0042] Transmission module; the transmission module is used to send the warning information notification obtained by the warning module 3 to the cloud server 8, wherein the transmission module includes a mobile communication module 4, a Wifi module 5, and a Bluetooth module 6;

[0043] The cloud server 8 is connected to the vital sign monitoring device 7 via a wireless network, the respiratory rate detection module 1 and the heart rate detection module 2 are connected to the early warning module 3, and the early warning module 3 is connected to the transmission module.

[0044] A non-contact vital sign early warning method specifically comprises the following steps:

[0045] S1, when a person enters the detection range of the non-contact vital signs monitoring device 7 and remains calm, the breathing rate of the human body is monitored in real time by the breathing detection module, and the heart rate detection module 2 is used to monitor the heart rate of the human body in real time;

[0046] The respiratory rate detection module 1 and the heart rate detection module 2 include a non-contact radar signal transceiver mechanism and a digital signal processing, and transmit a pulse signal through a radar transmission mechanism and receive radar echo signal data; then the radar echo data are subjected to time domain slow time multi-stage filtering and frequency domain Fourier transform, and finally the respiratory frequency and the heart rate are calculated respectively through time domain peak finding and spectrum analysis, and the respiratory frequency and the heart rate are calculated respectively through time domain peak finding and spectrum analysis, which specifically includes the following processes;

[0047] Peak search in time domain: Use three cascaded second-order filters on slow-time echo data; the time interval between two peaks or two troughs is considered as a breathing cycle; when the calculated frequency is less than the minimum frequency or greater than the maximum frequency, the final breathing frequency is calculated using the average of multiple accumulated breathing frequencies;

[0048] Spectral analysis: Use 6-cascade second-order filtering of slow-time echo data; use EMD (empirical mode decomposition) to divide the processed data; estimate the final heart rate based on the accumulated heart rate spectrum;

[0049] S2, setting warning parameters, the warning module 3 determines the current vital signs of the human body according to the respiratory frequency and heart rate of the human body within the accumulated time period;

[0050] Judging the current vital signs of the human body includes the following process: setting a period of time T as the observation period of the human body's vital signs, when the respiratory rate exceeds the threshold a1 during the observation period, and occurs more than a2 times, a warning message of too high respiratory rate is issued; when the respiratory rate is lower than the threshold b1 during the observation period, and continues for more than b2 time, and the number of occurrences exceeds b3 times, a warning message of too low respiratory rate is issued; when the heart rate exceeds the threshold c1 during the observation period, and occurs more than c2 times, a warning message of too high heart rate is issued; when the heart rate exceeds the threshold d1 during the observation period, and occurs more than d2 times, a warning message of too low heart rate is issued. Judging the current vital signs of the human body specifically includes the following judgment process:

[0051] Get the time series data set of human heart rate and respiratory rate in the time period T, which are RR = {rr1, rr2, ..., rr n}, HR={hr1, hr2,..., hr m}, 1≤n, m≤T;

[0052] If Count(rr 1，...，n≥a1)≥a2, that is, when the respiratory rate exceeds the threshold a1 during the observation period and exceeds a2 times, a high respiratory rate warning is issued;

[0053] If Count(rr 1，...，n ≤b1)≥b2, that is, when the respiratory rate is lower than the threshold value b1 within the observation period and exceeds b2 seconds continuously, and occurs more than b3 times, a low respiratory rate warning is issued;

[0054] If Count(hr 1，...，m ≥c1)≥c2, that is, when the heart rate exceeds the threshold value c1 during the observation period and exceeds c2 times, a high heart rate warning is triggered;

[0055] If Count(hr 1，...，m ≤d1)≥d2, that is, when the heart rate is lower than the threshold value d1 during the observation period and occurs more than d2 times, a low heart rate warning is issued;

[0056] S3, uploading the current vital signs of the human body determined by the early warning module 3 to the cloud server 8 through the transmission module for early warning notification;

[0057] The transmission module uploads the information to the cloud server 8 through one or more of the mobile communication module 4, the Wifi module 5, and the Bluetooth module 6 for early warning notification;

[0058] S4, the cloud server 8 will store the respiratory rate and heart rate of the monitored person for a long time, then correct and store the warning parameters, and periodically send them to the vital signs monitoring device 7 for replacement;

[0059] The cloud server 8 receives the long-term respiratory rate and heart rate data of the human body through the early warning module 3, and corrects the threshold values ​​a1, b1, c1 and d1 of the respiratory rate and heart rate early warning parameters of the human body, and archives the threshold values ​​a1, b1, c1 and d1. At the same time, the threshold values ​​a1, b1, c1 and d1 are sent to the vital signs monitoring device 7 for replacement; the cloud server 8 will receive the vital signs data of a single user's sleep at night collected by the vital signs monitoring equipment every day, and after removing the abnormal data, calculate the minimum and maximum values ​​of two types of important parameter indicators, and then accumulate the important parameter indicator values ​​for a period of time to fuse and calculate the early warning parameters, and finally retain the early warning parameters on the cloud server 8 to periodically correct the respiratory rate and heart rate early warning parameters. For example, extract the user's vital sign data from 22:00 to 06:00 on a single day, divide the respiratory rate and heart rate data sets according to the decile method, remove the data in the first decile and the tenth decile, and then calculate the minimum and maximum values ​​of the respiratory rate data set, and the minimum and maximum values ​​of the heart rate data set; take a time interval of one month as the fusion calculation period, calculate the four average values ​​of the two important parameters of "minimum respiratory rate", "maximum respiratory rate", "minimum heart rate" and "maximum heart rate" within the interval days, and use them as respiratory rate warning parameters a1, b1 and heart rate warning parameters c1, d1 respectively; finally, periodically calculate and correct the respiratory rate and heart rate warning parameters according to the set time interval. In addition, after each correction, the cloud server 8 will send instructions to the corresponding user vital sign monitoring device 7, and replace the warning parameter values ​​of the local warning module 3 system.

[0060] An electronic device comprises a processor and a storage device;

[0061] The storage device stores a computer program, and the processor executes the computer program to perform the above-mentioned vital sign warning method.

[0062] A computer storage medium includes a computer program and data stored therein. When the computer program is executed by a processor, the above-mentioned vital sign early warning method is implemented.

[0063] With the characteristics of safety, reliability, high accuracy and strong universality, the real-time monitoring method enables the guardian to capture the changing trend of the patient's vital signs at the first time, so as to discover potential danger signals earlier, predict the condition and take targeted measures. At the same time, by analyzing a large amount of monitoring data over a long period of time, it can also help doctors summarize the rules, optimize the diagnosis and treatment plan, and further improve the success rate of treatment.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A non-contact vital sign warning device, characterized in that: The non-contact vital sign warning device comprises a vital sign monitoring device and a cloud server, wherein the vital sign monitoring device comprises: A respiratory rate detection module, wherein the respiratory rate detection module is used to calculate the respiratory frequency; Heart rate detection module; the heart rate detection module is used to calculate the heart rate; Early warning module; the early warning module is used to receive information about respiratory rate and heart rate and process it to obtain early warning information; Transmission module; the transmission module is used to send the warning information notification obtained by the warning module to the cloud server; The cloud server is used to store the respiratory rate and heart rate of the monitored person, and then correct and store the warning parameters, and periodically send them to the vital signs monitoring device for parameter replacement; The cloud server is connected to the vital sign monitoring device via a wireless network, the respiratory rate detection module and the heart rate detection module are connected to the early warning module, and the early warning module is connected to the transmission module; Among them, the transmission module includes a mobile communication module, a Wifi module, and a Bluetooth module.

2. A non-contact vital sign warning method according to any one of claims 1, characterized in that: The specific steps include: S1. When a person enters the detection range of the non-contact vital signs monitoring device and remains calm, the breathing rate of the person is monitored in real time by the breathing detection module, and the heart rate detection module is used to monitor the heart rate of the person in real time; S2. Setting warning parameters, the warning module determines the current vital signs of the human body according to the respiratory rate and heart rate of the human body within the accumulated time period; S3, uploading the current vital signs of the human body determined by the early warning module to the cloud server for early warning notification through the transmission module; S4. The cloud server will store the respiratory rate and heart rate of the person being monitored for a long time, and then correct and store the warning parameters, and periodically send them to the vital signs monitoring device for replacement.

3. A non-contact vital sign warning method according to claim 2, characterized in that: In step S1, the respiratory rate detection module and the heart rate detection module include a non-contact radar signal transceiver mechanism and a digital signal processing, a pulse signal is transmitted through the radar transmission mechanism, and radar echo signal data is received; then the radar echo data is subjected to time domain slow time multi-stage filtering and frequency domain Fourier transform, and finally the respiratory rate and the heart rate are calculated respectively through time domain peak finding and spectrum analysis, and the respiratory rate and the heart rate are calculated respectively through time domain peak finding and spectrum analysis, which specifically includes the following processes; Peak finding in time domain: using three cascaded second-order filters of slow-time echo data; The time interval between two peaks or two troughs is regarded as a breathing cycle; when the calculated frequency is less than the minimum frequency or greater than the maximum frequency, the final breathing frequency is calculated using the average of the accumulated multiple breathing frequencies; Spectral analysis: Use 6-cascade second-order filtering of slow-time echo data; use EMD (empirical mode decomposition) to divide the processed data; estimate the final heart rate based on the accumulated heart rate spectrum.

4. A non-contact vital sign warning method according to claim 2, characterized in that: In step S2, the current vital signs of the human body are determined. The process includes the following steps: a period of time T is set as a human vital sign observation period, and when the respiratory rate exceeds a threshold a1 within the observation period and exceeds a2 times, a high respiratory rate warning message is issued; When the respiratory rate is lower than the threshold b1 during the observation period and lasts for more than b2 time, and the number of occurrences exceeds b3 times, a warning message of low respiratory rate is issued; When the heart rate exceeds the threshold value c1 during the observation period and exceeds the threshold value c2 times, a high heart rate warning message is issued; When the heart rate exceeds the threshold value d1 during the observation period and occurs more than d2 times, a low heart rate warning message is issued.

5. The non-contact vital sign warning method according to claim 2, characterized in that: In step S3, the transmission module uploads the information to the cloud server through one or more of the mobile communication module, Wifi module, and Bluetooth module for early warning notification.

6. A non-contact vital sign warning method according to claim 2, characterized in that: In step S4, the cloud server receives the long-term respiratory rate and heart rate data of the human body through the early warning module, and corrects the threshold values ​​a1, b1, c1 and d1 of the respiratory rate and heart rate early warning parameters of the human body, and archives the threshold values ​​a1, b1, c1 and d1. At the same time, the threshold values ​​a1, b1, c1 and d1 are sent to the vital signs monitoring device for replacement.

7. A non-contact vital sign warning method according to claim 4, characterized in that: The determination of the current vital signs of the human body specifically includes the following determination process: Get the time series data set of human heart rate and respiratory rate in the time period T, respectively RR={rr1,rr2,...,rr n },HR={hr1,hr2,...,h rn },1≤n,m≤T; If Count(rr 1，...，n ≥a1)≥a2, that is, when the respiratory rate exceeds the threshold a1 during the observation period and exceeds a2 times, a high respiratory rate warning is issued; If Count(rr 1，…n ≤b1)≥b2, that is, when the respiratory rate is lower than the threshold value b1 within the observation period and exceeds b2 seconds continuously, and occurs more than b3 times, a low respiratory rate warning is issued; If Count(hr 1…，m ≥c1)≥c2, that is, when the heart rate exceeds the threshold value c1 during the observation period and exceeds c2 times, a high heart rate warning is triggered; If Count(hr 1，…，m ≤d1)≥d2, that is, when the heart rate during the observation period is lower than the threshold d1 and occurs more than d2 times, a low heart rate warning is issued.

8. The non-contact vital sign warning method according to claim 5, characterized in that: The cloud server will receive the vital sign data of a single user's sleep at night collected by the vital sign monitoring equipment every day, and after removing the abnormal data, calculate the minimum and maximum values ​​of two types of important parameter indicators, and then accumulate the important parameter indicator values ​​for a period of time to fuse and calculate the early warning parameters, and finally retain the early warning parameters on the cloud server side to periodically correct the respiratory rate and heart rate early warning parameters. For example, extract the user's vital sign data from 22:00 to 06:00 on a single day, divide the respiratory rate and heart rate data sets according to the decile method, remove the data in the first decile and the tenth decile, and then calculate the minimum and maximum values ​​of the respiratory rate data set, and the minimum and maximum values ​​of the heart rate data set; take a time interval of one month as the fusion calculation cycle, calculate the four average values ​​of the two important parameters of "minimum respiratory rate", "maximum respiratory rate", "minimum heart rate", and "maximum heart rate" within the interval days, and use them as respiratory rate warning parameters a1, b1 and heart rate warning parameters c1, d1 respectively; finally, periodically calculate and correct the respiratory rate and heart rate warning parameters according to the set time interval. In addition, after each correction, the cloud server will send instructions to the corresponding user's vital sign monitoring device and replace the warning parameter values ​​of the local warning module system.

9. An electronic device, characterized in that: including a processor and a storage device; The storage device stores a computer program, and the processor executes the computer program to perform the method according to any one of claims 2 to 8.

10. A computer storage medium, comprising a computer program and data stored therein, wherein the computer program, when executed by the processor, implements the method described in any one of 2-8.

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